Copy-move forgery detection techniques based on traditional methods in digital images
Subject Areas : Communication Engineeringmaryam attaie 1 , Azar Mahmoodzadeh 2
1 - گروه اموزشی برق، دانشگاه ازاد اسلامی واحد شیراز
2 - Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
Keywords: Copy-Move Image Forgery, Forgery Detection, Image Processing, Digital Image,
Abstract :
Image forgery is one of the most widely used fields in image processing, which has been widely studied and studied by researchers. There are different types of digital image forgery, copy-move forgery is one of the common examples, and it is very important to recognize this type of forgery. In this review article, while introducing the concepts of copy-move image forgery, the steps, classification of detection methods and research bias in this field have been discussed. This article can open the way for image processing researchers in the process of detecting copy- move forgery. The authors' effort has been to explore all aspects of this process.
References:
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[1] B. Soni, P. K. Das, and D. M. Thounaojam, "CMFD: a detailed review of block based and key feature based techniques in image copy‐move forgery detection," IET Image Processing, vol. 12, pp. 167-178, 2018.
[2] A. Dixit and R. Gupta, "Copy-Move Image Forgery Detection a Review," International Journal of Image, Graphics and Signal Processing, vol. 8, p. 29, 2016.
[3] M. A. Qureshi and M. Deriche, "A review on copy move image forgery detection techniques," in 2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14), 2014, pp. 1-5.
[4] N. T. Pham and C.-S. Park, "Toward Deep-Learning-Based Methods in Image Forgery Detection: A Survey," IEEE Access, vol. 11, pp. 11224-11237, 2023.
[5] A. Bensaad, K. Loukhaoukha, and S. Sadoudi, "Keypoint-based copy-move forgery detection in digital images: a survey," in 2022 7th International Conference on Image and Signal Processing and their Applications (ISPA), 2022, pp. 1-6.
[6] K. M. Hosny, A. M. Mortda, M. M. Fouda, and N. A. Lashin, "An efficient CNN model to detect copy-move image forgery," IEEE Access, vol. 10, pp. 48622-48632, 2022.
[7] D. Chauhan, D. Kasat, S. Jain, and V. Thakare, "Survey on keypoint based copy-move forgery detection methods on image," Procedia Computer Science, vol. 85, pp. 206-212, 2016.
[8] B. Ustubioglu, G. Tahaoglu, and G. Ulutas, "Detection of audio copy-move-forgery with novel feature matching on Mel spectrogram," Expert Systems with Applications, vol. 213, p. 118963, 2023.
[9] N. Kumar and T. Meenpal, "Salient keypoint-based copy–move image forgery detection," Australian Journal of Forensic Sciences, vol. 55, pp. 331-354, 2023.
[10] D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International journal of computer vision, vol. 60, pp. 91-110, 2004.
[11] Y. Fan, Y.-S. Zhu, and Z. Liu, "An improved SIFT-based copy-move forgery detection method using T-linkage and multi-scale analysis," Journal of Information Hiding and Multimedia Signal Processing, vol. 7, pp. 399-408, 2016.
[12] R. C. Pandey, S. K. Singh, K. Shukla, and R. Agrawal, "Fast and robust passive copy-move forgery detection using SURF and SIFT image features," in 2014 9th International conference on industrial and information systems (ICIIS), 2014, pp. 1-6.
[13] I. Amerini, L. Ballan, R. Caldelli, A. Del Bimbo, and G. Serra, "A sift-based forensic method for copy–move attack detection and transformation recovery," IEEE transactions on information forensics and security, vol. 6, pp. 1099-1110, 2011.
[14] A. C. Popescu and H. Farid, "Exposing digital forgeries by detecting duplicated image regions," Dept. Comput. Sci., Dartmouth College, Tech. Rep. TR2004-515, pp. 1-11, 2004.
[15] A. J. Fridrich, B. D. Soukal, and A. J. Lukáš, "Detection of copy-move forgery in digital images," in in Proceedings of Digital Forensic Research Workshop, 2003.
[16] Z. H.-N. a. M. Nasri, "Copy-Move Image Forgery Detection Using Redundant Keypoint Elimination Method," in Cryptographic and Information Security Approaches for Images and Videos, S. Ramakrishnan, Ed. Boca Raton: CRC Press, pp. 773-797, 2019.
[17] C.-C. Chen, W.-Y. Lu, and C.-H. Chou, "Rotational copy-move forgery detection using SIFT and region growing strategies," Multimedia Tools and Applications, pp. 1-16, 2019.
[18] J. Li, X. Li, B. Yang, and X. Sun, "Segmentation-based image copy-move forgery detection scheme," IEEE Transactions on Information Forensics and Security, vol. 10, pp. 507-518, 2014.
[19] S. Prasad and B. Ramkumar, "Passive copy-move forgery detection using SIFT, HOG and SURF features," in 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 2016, pp. 706-710.
[20] H. Bay, T. Tuytelaars, and L. Van Gool, "Surf: Speeded up robust features," in Computer vision–ECCV 2006, ed: Springer, 2006, pp. 404-417.
[21] M. F. Hashmi, V. Anand, and A. G. Keskar, "A copy-move image forgery detection based on speeded up robust feature transform and Wavelet Transforms," in 2014 international conference on computer and communication technology (ICCCT), 2014, pp. 147-152.
[22] C. Wang, Z. Zhang, Q. Li, and X. Zhou, "An image copy-move forgery detection method based on SURF and PCET," IEEE Access, vol. 7, pp. 170032-170047, 2019.
[23] M. Bilal, H. A. Habib, Z. Mehmood, T. Saba, and M. Rashid, "Single and multiple copy–move forgery detection and localization in digital images based on the sparsely encoded distinctive features and DBSCAN clustering," Arabian Journal for Science and Engineering, vol. 45, pp. 2975-2992, 2020.
[24] A. Badr, A. Youssif, and M. Wafi, "A robust copy-move forgery detection in digital image forensics using SURF," in 2020 8th International Symposium on Digital Forensics and Security (ISDFS), 2020, pp. 1-6.
[25] R. Rakhi, A. J. Sundararaj, R. C. Joy, and J. J. Winston, "Effective Detection of Copy Move Forgery Using Surf," in 2023 4th International Conference on Signal Processing and Communication (ICSPC), 2023, pp. 306-310.
[26] E. Rosten, R. Porter, and T. Drummond, "Faster and better: A machine learning approach to corner detection," IEEE transactions on pattern analysis and machine intelligence, vol. 32, pp. 105-119, 2008.
[27] B. Fatima, A. Ghafoor, S. S. Ali, and M. M. Riaz, "FAST, BRIEF and SIFT based image copy-move forgery detection technique," Multimedia Tools and Applications, vol. 81, pp. 43805-43819, 2022.
[28] G. Muzaffer, O. Makul, B. Ustubioglu, and G. Ulutas, "Copy move forgery detection using gabor filter and orb," in Proc. 2016International Conf. Image Process. Prod. Comput. Sci, 2016, pp. 23-29.
[29] V. Mehta, A. K. Jaiswal, and R. Srivastava, "Copy-move image forgery detection using DCT and ORB feature set," in Futuristic Trends in Networks and Computing Technologies: Second International Conference, FTNCT 2019, Chandigarh, India, November 22–23, 2019, Revised Selected Papers 2, 2020, pp. 532-544.
[30] Z. Xue, L. Tian, and C. Li, "Passive Image Copy–Move Forgery Detection Based on ORB Features," in Recent Developments in Intelligent Computing, Communication and Devices: Proceedings of ICCD 2019 5, 2021, pp. 312-317.
[31] K.-T. Huynh, T.-N. Ly, and T. Le-Tien, "ORB for Detecting Copy-Move Regions with Scale and Rotation in Image Forensics," in Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications: 7th International Conference, FDSE 2020, Quy Nhon, Vietnam, November 25–27, 2020, Proceedings 7, 2020, pp. 358-372.
[32] Y. Zhu, X. Shen, and H. Chen, "Copy-move forgery detection based on scaled ORB," Multimedia Tools and Applications, vol. 75, pp. 3221-3233, 2016.
[33] X. Guo, X. Cao, J. Zhang, and X. Li, "Mift: A mirror reflection invariant feature descriptor," in Asian Conference on Computer Vision, 2009, pp. 536-545.
[34] M. Jaberi, G. Bebis, M. Hussain, and G. Muhammad, "Accurate and robust localization of duplicated region in copy–move image forgery," Machine vision and applications, vol. 25, pp. 451-475, 2014.
[35] M. Jaberi, G. Bebis, M. Hussain, and G. Muhammad, "Improving the detection and localization of duplicated regions in copy-move image forgery," in 2013 18th international conference on digital signal processing (DSP), 2013, pp. 1-6.
[36] V. Agarwal and V. Mane, "Reflective SIFT for improving the detection of copy-move image forgery," in 2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), 2016, pp. 84-88.
[37] V. Dhania and H. B. KP, "Improving Digital Image Forgery Detection Using MIFT Features and Adaptive Over Segmentation," 2016.
[38] A. J. Mariyal, "AN EFFICIENT IMAGE FORGERY DETECTION USING SIFT AND MIFT."
[39] P. F. Alcantarilla, A. Bartoli, and A. J. Davison, "KAZE features," in European conference on computer vision, 2012, pp. 214-227.
[40] A. Rani and A. Jain, "Copy-Move Image Forgery Detection Using SURF, SIFT, and KAZE," in Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication: MARC 2021, 2022, pp. 719-726.
[41] D. Vaishnavi, G. Balaji, and D. Mahalakshmi, "KAZE feature based passive image forgery detection," in First International Conference on Artificial Intelligence and Cognitive Computing: AICC 2018, 2019, pp. 333-340.
[42] A. Kaur, S. Walia, and K. Kumar, "Comparative analysis of different keypoint based copy-move forgery detection methods," in 2018 Eleventh International Conference on Contemporary Computing (IC3), 2018, pp. 1-5.
[43] F. Yang, J. Li, W. Lu, and J. Weng, "Copy-move forgery detection based on hybrid features," Engineering Applications of Artificial Intelligence, vol. 59, pp. 73-83, 2017.
[44] P. Alcantarilla, J. Nuevo, and A. Bartoli, "Fast explicit diffusion for accelerated features in nonlinear scale spaces british machine vision conference (BMVC)," ed: Bristol, 2013.
[45] A. Dixit and S. Bag, "Composite attacks‐based copy‐move image forgery detection using AKAZE and FAST with automatic contrast thresholding," IET Image Processing, vol. 14, pp. 4528-4542, 2020.
[46] X. Zhou and Q. Shi, "Multiple copy-move forgery detection based on density clustering," Pattern Recognition and Image Analysis, vol. 31, pp. 109-116, 2021.
[47] C. S. Prakash, P. P. Panzade, H. Om, and S. Maheshkar, "Detection of copy-move forgery using AKAZE and SIFT keypoint extraction," Multimedia Tools and Applications, vol. 78, pp. 23535-23558, 2019.
[48] S. K. Narasimhamurthy, V. K. Mahadevachar, and R. K. T. Narasimhamurthy, "A Copy-Move Image Forgery Detection Using Modified SURF Features and AKAZE Detector," International Journal of Intelligent Engineering & Systems, vol. 16, 2023.
[49] S. Kumar, J. Desai, and S. Mukherjee, "A fast DCT based method for copy move forgery detection," in 2013 IEEE Second International Conference on Image Information Processing (ICIIP-2013), 2013, pp. 649-654.
[50] E. A. Armas Vega, E. González Fernández, A. L. Sandoval Orozco, and L. J. García Villalba, "Copy-move forgery detection technique based on discrete cosine transform blocks features," Neural Computing and Applications, vol. 33, pp. 4713-4727, 2021.
[51] M. A. S. Kumar, "IMAGE FORENSIC FOR DIGITAL IMAGE COPY MOVE FORGERY DETECTION," IMAGE, vol. 52, 2023.
[52] A. Shankar, P. Swetha, and B. Ramu, "Image Forgery Detection Method for Copy-Move and Splicing Attacks Using DCT, DWT And Correlation," Journal of Pharmaceutical Negative Results, pp. 3878-3883, 2022.
[53] S. Khan and A. Kulkarni, "Reduced time complexity for detection of copy-move forgery using discrete wavelet transform," International Journal of Computer Applications, vol. 6, pp. 31-36, 2010.
[54] S. Mushtaq, R. A. Khan, S. A. Lone, A. Moon, and M. Qadri, "Improved Complexity in Localization of Copy-Move Forgery Using DWT," in International Conference on Computing, Communications, and Cyber-Security, 2022, pp. 825-839.
[55] R. Ashraf, M. S. Mehmood, T. Mahmood, J. Rashid, M. W. Nisar, and M. Shah, "An efficient forensic approach for copy-move forgery detection via discrete wavelet transform," in 2020 International Conference on Cyber Warfare and Security (ICCWS), 2020, pp. 1-6.
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